Correlates of Hepatitis C Virus Infection in the Targeted Testing Program of the New York City Jail System: Epidemiologic Patterns and Priorities for Action. (January 2017) - Akiyama, Matthew J.; Kaba, Fatos; Rosner, Zachary; Alper, Howard; Kopolow, Aimee; Litwin, Alain H.; Venters, Homer; MacDonald, Ross
Objective: The objective of this study was to understand predictors of hepatitis C virus (HCV) antibody positivity in a large urban jail system in New York City. Methods: We examined demographic characteristics, risk behaviors, and HCV antibody prevalence among 10 790 jail inmates aged 16 to 86 who were screened from June 13, 2013, to June 13, 2014, based on birth cohort or conventional high-risk criteria. We used logistic regression analysis to determine predictors of HCV antibody positivity. Results: Of the 10 790 inmates screened, 2221 (20.6%) were HCV antibody positive. In the multivariate analysis, HCV antibody positivity was associated most strongly with injection drug use (IDU; adjusted odds ratio [aOR] = 35.0; 95% confidence interval [CI], 28.5-43.0). Women were more likely than men to be infected with HCV (aOR = 1.3; 95% CI, 1.1-1.5). Compared with non-Hispanic black people, Hispanic (aOR = 2.1; 95% CI, 1.8-2.4) and non-Hispanic white (aOR = 1.7; 95% CI, 1.5-2.1) people were more likely to be infected with HCV. Non-IDU, recidivism, HIV infection, homelessness, mental illness, and lower education level were all significantly associated with HCV infection. The prevalence rate of HCV infection among a subset of inmates born after 1965 who denied IDU and were not infected with HIV was 5.6% (198 of 3529). Predictors of HCV infection among this group included non-IDU as well as being non-Hispanic white, Hispanic, recidivist, and homeless. Conclusion: These data reveal differences in HCV infection by sex, race/ethnicity, and socioeconomics in a large jail population, suggesting that a focused public health intervention is required and that universal screening may be warranted. Further sensitivity and cost-benefit analyses are needed to make this determination.